AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

An analysis of the passenger to cabin crew ratio and exit reliability based on past survivable aviation accidents

A hotly debated issue in the area of aviation safety is the number of cabin crew members required to evacuate an aircraft in the event of an emergency. Most countries regulate the minimum number required for the safe operation of an aircraft, but these rulings are based on little if any scientific evidence. Another issue of concern is the failure rate of exits and slides. This paper examines these issues using the latest version of Aircraft Accident Statistics and Knowledge database AASK V4.0, which contains information from 105 survivable crashes and more than 2,000 survivors, including accounts from 155 cabin crew members.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.

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Leadership and management standards in the UK Lifelong Learning sector

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Can evidence-based healthy housing interventions be put into practice in the UK's private housing sector?

The UK’s public health agenda has encouraged enhanced housing and health interventions. The private housing sector (privately rented and owner occupied) is the favoured and majority UK tenure, but is it seen as a primarily health promoting environment, or a commercial asset? There has been a growing interest in integrating health and housing policy in recent years. However, housing and public health fall under separate government departments and funding regimes. Partnership working has sought to overcome silo working and encourage evidence-based practice, yet is particularly challenging for interventions in the private housing sector, with an increased emphasis on ‘personal responsibility’ for conditions. Strategic public health frameworks are in place, but barriers remain and there is pressure for organisations to revert to core activities. An accessible, continually updated evidence base specific to private sector housing is recommended, to help estimate health gain arising from interventions to prioritise activities and address inequalities.

Trade credit linkages along the supply chain: evidence for the Italian textile sector

We examine the trade credit linkages among firms within a supply chain to reckon the effect of such linkages on the propagation of liquidity shocks from downstream to upstream firms. We choose a sample appropriate for this task, consisting of a large data set of Italian firms from the textile industry, a well known example of a comprehensive manufacturing cluster featuring a large number of small and specialized firms at each level of the supply chain. The results of the analysis indicate that the level of trade credit that firms provide to their suppliers is positively related to the level of trade credit granted to their clients: when the level of trade credit granted to clients divided by sales goes up by 1, the level of trade credit provided to suppliers divided by cost-of goods-sold goes up by an amount that varies between 0,22 and 0,52. Since all firms along the chain are linked by trade credit relationships, an increase in the level of trade credit granted by wholesalers generates a liquidity cascade throughout the chain. We designate the overall increase in the level of trade credit among all firms in the chain as a result of a unitary impulse in the level of trade credit granted by wholesalers as the multiplier effect of trade credit for the industry chain. We estimate such multiplier to vary between 1.28 and 2.04. We also investigate the effect of final demand on the level of trade credit sourced by firms at various levels of the chain and, in particular, whether such effect is amplified for firms further up in the chain as a result of liquidity propagation via trade credit linkages. We uncover evidence of such amplification when the links of liquidity transmission along the chain are individually modeled and estimated. An unitary increase in wholesalers’ sales is found to produce an effect on trade payables among firms at the top of the chain (i.e., Preparers and Spinners) that is more than twice as big as the corresponding effect among firms at the bottom of the chain (i.e., Wholesalers).

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